Data analysis

We investigate large functional genomics and high-throughput biological datasets. Assistance is provided in experimental design and subsequent analysis of next-generation sequencing, microarray, and mass-spectrometry-based proteomics experiments. The current focus is on the analysis of small RNA-Seq, mRNA-Seq and haploid ES cell screen data. Gene lists derived from publicly available studies or generated from in-house high-throughput experiments (NGS, microarray, proteomics) are analyzed for the overrepresentation of pathways, GO-terms, functional domains, or placed in interaction networks to visualize their relationships. Genome-wide expression patterns are contextualized with known processes and pathways using Gene Set Enrichment Analysis (GSEA). Local instances of integrated model organism databases and genome annotation portals permit visualization and analysis of in-house data with dedicated resources and additional privacy. User-driven data exploration is supported by the Ingenuity Pathway Analysis System. Project-specific hands-on trainings on applications for computational biology is provided on individual basis.

Data Analysis Infrastructure

We provide access to a number of complete data analysis workflows with extensive result reporting to aid the biological interpretation of NGS data (RNA-seq, ChIP-seq, smRNA-seq). For detailed instructions on pipeline usage please refer to the Protocols section.